Building smarter, safer healthcare: The role of technology partners in AI adoption
Artificial intelligence is evolving from hype and speculation to practical applications in healthcare technology. As I detailed earlier this year, the opportunities are endless and the potential pitfalls are real.
As healthcare organizations begin to examine how to integrate artificial intelligence into their workflows, it is necessary to consider best practices for adoption with their technology partners.
Innovate and consider risk reduction
McKinsey’s 2025 Technology Outlook calls AI an “accelerator” for innovation; I tend to agree, but there need to be boundaries around transparency, levels of automation, and how AI is regulated.
The U.S. “Artificial Intelligence Action Plan” launched by the White House in July is centered on innovation and focuses less on risk mitigation than the EU’s Artificial Intelligence Act.
Health technology innovators must focus on both: innovation and risk mitigation. Because, in healthcare, trust is currency. Every tool that leverages AI must be built with compliance, security, and regulatory readiness in mind.
Partners You can start small but make a big impact
Technology partners should view their products as a way to help healthcare organizations realize their own AI vision. With interoperability and data supported by security measures and compliance knowledge, industry can enable frictionless operations that inform care, routing and compliance in new ways.
Artificial intelligence can become an additional layer within the solutions currently in use. Rather than overhauling or replacing solutions, technology partners can consider how AI can support and enhance operations, workflows or cost efficiencies and make a huge impact while maintaining security and compliance.
Intentional Implementation: MEG Method
AI adoption should not be an end in itself. To ensure that each initiative delivers measurable value, technology leaders can adopt a structured approach like the MEG framework: Maintain, Experience, and Grow.
- maintain Covers what must be done – the foundational investments needed to ensure reliability, compliance and security.
- experience Represents what it should do—improvements that enhance usability, trust, and long-term differentiation.
- grow Driving new initiatives – AI-driven innovation is directly linked to clear ROI and measurable results.
By sequencing investments in this way, organizations can integrate AI responsibly, balancing innovation with stability and trust.
Tools to achieve this
To reduce friction, save time, and create quality experiences, technology partners must adopt key tools and practices to enable AI innovation at scale, including comprehensive API documentation, strong FHIR adoption, and defined data retention and security policies
With these foundational components in place, technology partners can help providers spend less time on administrative tasks and more time on patient care, and help payers and pharmaceutical companies gain a clearer understanding of ROI, adherence outcomes and real-world evidence. It can also help health technology providers scale faster and more securely.
With the right tools and partners, AI can be used to focus on scale, savings and informed decision-making. Imagine being able to view prescription price transparency and provide personalized and easy-to-understand medication information directly to patients through AI analysis of available coupons. AI can also significantly reduce callbacks regarding previous authorizations, pharmacy routing and follow-up questions
As I reflect on the future trajectory, I feel energized by the possibilities of incorporating AI into technology to bring measurable value and seamless workflows to healthcare. If technology partners can safely use AI to help make better, faster, and more transparent decisions across the continuum of care, then we’ve done our job. If we remember to start with the patient first, we can solve the right problems.
Photo: Gerasimov174, Getty Images
Julian Herbert began his career in technology product development as a business analyst focusing on e-commerce in the semiconductor industry. Out of curiosity, he became a management consultant with Deloitte, where he led M&A divestitures and integrations in a variety of industries, including pharmaceuticals and biotech. He then returned to product development and e-commerce at Amazon, launching machine learning solutions for third-party sellers on the platform. Julian also led product development for AWS Startups, building their first micro-targeting product line.
At DoseSpot, Julian leads product innovation, helping the company grow and deliver safe and reliable e-prescribing technology and software integration across multiple healthcare markets. Originally from Louisiana, Julian graduated as valedictorian from Southern University in Baton Rouge with a bachelor's degree in computer science. He also holds an MBA from the University of Michigan's Ross School of Business, where he focused on strategy and entrepreneurship.
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